Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of ISMA 2018 |
| Subtitle of host publication | International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics |
| Editors | D. Moens, W. Desmet, B. Pluymers, W. Rottiers |
| Pages | 5157-5167 |
| Number of pages | 11 |
| ISBN (electronic) | 9789073802995 |
| Publication status | Published - 2018 |
| Event | 28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018 - Leuven, Belgium Duration: 17 Sept 2018 → 19 Sept 2018 |
Publication series
| Name | Proceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics |
|---|
Abstract
Uncertainty quantification metrics are critical in the campaign of stochastic model updating, by provide an elaborate measurement of the uncertainty in both simulations and experiments. In this work, the Bhattacharyya distance is proposed as a comprehensive model updating metric for two samples considering their probabilistic properties. The updating process employs a two-steps Bayesian framework where the Bhattacharyya distance is well embedded and its performance is compared with the Euclidian distance. The Euclidian distance is utilized as metric in the first step where the geometry distance between the center points of the numerical and experimental samples are calculated. The posteriori distributions of the means are subsequently transferred to the second step where the Bhattacharyya distance is utilized as metric with the main effort to update the distributional coefficients of parameters. The feasibility of the overall two-step framework and the advantage of the Bhattacharyya distance metric are demonstrated in a simulated example.
ASJC Scopus subject areas
- Engineering(all)
- Mechanical Engineering
- Engineering(all)
- Mechanics of Materials
- Physics and Astronomy(all)
- Acoustics and Ultrasonics
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Proceedings of ISMA 2018: International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics. ed. / D. Moens; W. Desmet; B. Pluymers; W. Rottiers. 2018. p. 5157-5167 (Proceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Bayesian model updating using stochastic distances as uncertainty quantification metrics
AU - Bi, Sifeng
AU - Broggi, Matteo
AU - Beer, Michael
AU - Zhang, Yuguang
N1 - Funding Information: This work is supported by the Alexander von Humboldt Foundation, which is greatly appreciated by the first author.
PY - 2018
Y1 - 2018
N2 - Uncertainty quantification metrics are critical in the campaign of stochastic model updating, by provide an elaborate measurement of the uncertainty in both simulations and experiments. In this work, the Bhattacharyya distance is proposed as a comprehensive model updating metric for two samples considering their probabilistic properties. The updating process employs a two-steps Bayesian framework where the Bhattacharyya distance is well embedded and its performance is compared with the Euclidian distance. The Euclidian distance is utilized as metric in the first step where the geometry distance between the center points of the numerical and experimental samples are calculated. The posteriori distributions of the means are subsequently transferred to the second step where the Bhattacharyya distance is utilized as metric with the main effort to update the distributional coefficients of parameters. The feasibility of the overall two-step framework and the advantage of the Bhattacharyya distance metric are demonstrated in a simulated example.
AB - Uncertainty quantification metrics are critical in the campaign of stochastic model updating, by provide an elaborate measurement of the uncertainty in both simulations and experiments. In this work, the Bhattacharyya distance is proposed as a comprehensive model updating metric for two samples considering their probabilistic properties. The updating process employs a two-steps Bayesian framework where the Bhattacharyya distance is well embedded and its performance is compared with the Euclidian distance. The Euclidian distance is utilized as metric in the first step where the geometry distance between the center points of the numerical and experimental samples are calculated. The posteriori distributions of the means are subsequently transferred to the second step where the Bhattacharyya distance is utilized as metric with the main effort to update the distributional coefficients of parameters. The feasibility of the overall two-step framework and the advantage of the Bhattacharyya distance metric are demonstrated in a simulated example.
UR - http://www.scopus.com/inward/record.url?scp=85060367696&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85060367696
T3 - Proceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics
SP - 5157
EP - 5167
BT - Proceedings of ISMA 2018
A2 - Moens, D.
A2 - Desmet, W.
A2 - Pluymers, B.
A2 - Rottiers, W.
T2 - 28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018
Y2 - 17 September 2018 through 19 September 2018
ER -